Automated Author ProfileBlandin, Rémi
Blandin, Rémi
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.6 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset contains the synthetic stimuli used in the study published in the paper "A Comparative Study of 3D and 1D AcousticSimulations of the Higher Frequencies of Speech". The goal of this study was to evaluate the accuracy of the acoustic wave propagation in the vocal tract in a source-filter synthesis paradigm with two perceptual experiments. The high frequencies (above 4 kHz) of the stimuli weregenerated by three different methods: a source-filter method relying on a 1D and a 3D acoustic model, and a bandwith extension algorithm with no physical basis. The low frequency portion was generated with a 3D acoustic model in each case. The data and code used to generatethe stimuli are provided in this dataset.
Authors
- Blandin, Rémi ;
- Stone, Simon ;
- Remacle, Angélique ;
- Didone, Vincent ;
- Birkholz, Peter